CBravoR/AdvancedAnalyticsLabs

Analytics labs notebooks for Statistics and Business School students

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Established

Covers practical credit risk modeling workflows—from Weight of Evidence transformations and logistic regression scorecards to ensemble methods (Random Forest, XGBoost) with Shapley value explainability—alongside foundational topics in revenue management, Basel regulation, and bond pricing. Built on Jupyter notebooks with scikit-learn, XGBoost, and Polars, handling larger-than-memory datasets via SGD and streaming. Includes PD/LGD calibration using the Vasicek model and integrates SQLAlchemy for database connectivity.

No Package No Dependents
Maintenance 13 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 18 / 25

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33

Forks

16

Language

Jupyter Notebook

License

GPL-3.0

Last pushed

Mar 08, 2026

Commits (30d)

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